Markowetz Alexander, Błaszkiewicz Konrad, Montag Christian, Switala Christina, Schlaepfer Thomas E
Department of Computer Science, University of Bonn, Germany.
Department of Psychology, University of Bonn, Germany.
Med Hypotheses. 2014 Apr;82(4):405-11. doi: 10.1016/j.mehy.2013.11.030. Epub 2014 Jan 13.
For the first time in history, it is possible to study human behavior on great scale and in fine detail simultaneously. Online services and ubiquitous computational devices, such as smartphones and modern cars, record our everyday activity. The resulting Big Data offers unprecedented opportunities for tracking and analyzing behavior. This paper hypothesizes the applicability and impact of Big Data technologies in the context of psychometrics both for research and clinical applications. It first outlines the state of the art, including the severe shortcomings with respect to quality and quantity of the resulting data. It then presents a technological vision, comprised of (i) numerous data sources such as mobile devices and sensors, (ii) a central data store, and (iii) an analytical platform, employing techniques from data mining and machine learning. To further illustrate the dramatic benefits of the proposed methodologies, the paper then outlines two current projects, logging and analyzing smartphone usage. One such study attempts to thereby quantify severity of major depression dynamically; the other investigates (mobile) Internet Addiction. Finally, the paper addresses some of the ethical issues inherent to Big Data technologies. In summary, the proposed approach is about to induce the single biggest methodological shift since the beginning of psychology or psychiatry. The resulting range of applications will dramatically shape the daily routines of researches and medical practitioners alike. Indeed, transferring techniques from computer science to psychiatry and psychology is about to establish Psycho-Informatics, an entire research direction of its own.
有史以来第一次，有可能同时大规模且细致入微地研究人类行为。在线服务以及无处不在的计算设备，如智能手机和现代汽车，记录着我们的日常活动。由此产生的大数据为追踪和分析行为提供了前所未有的机会。本文假设大数据技术在心理测量学背景下对于研究和临床应用的适用性及影响。它首先概述了当前的技术水平，包括所产生数据在质量和数量方面的严重不足。接着提出了一个技术愿景，它由（i）众多数据源，如移动设备和传感器，（ii）一个中央数据存储库，以及（iii）一个分析平台组成，该平台采用数据挖掘和机器学习技术。为了进一步说明所提出方法的巨大益处，本文随后概述了两个当前项目，即记录和分析智能手机使用情况。其中一项此类研究试图由此动态量化重度抑郁症的严重程度；另一项研究则调查（移动）网络成瘾问题。最后，本文探讨了大数据技术所固有的一些伦理问题。总之，所提出的方法将引发自心理学或精神病学诞生以来最大的一次方法学转变。由此产生的一系列应用将极大地塑造研究人员和医学从业者的日常工作。的确，将计算机科学技术应用于精神病学和心理学即将建立起心理信息学，这是一个自成一体的完整研究方向。
